Evidence map›Paper›PMID 30552508›Full record

Observational studyLangenbeck's archives of surgery2019

Complex gastric surgery in Germany-is centralization beneficial? Observational study using national hospital discharge data.

Ulrike Nimptsch, Thomas Haist, Ines Gockel, Thomas Mansky, Dietmar Lorenz

Abstract readObservational Study
PubMed Publisher
In one paragraph

Observational study in Langenbeck's archives of surgery, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Predictors and Significance of Readmission after Esophagogastric Surgery: A Nationwide Analysis.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2024
    Article
  6. TREATMENT OF GASTRIC CANCER ACCORDING TO THE COMPLEXITY OF THE HOSPITAL ONCOLOGY UNIT: ANALYSIS OF 33,774 PATIENTS OVER TWO DECADES.Arquivos brasileiros de cirurgia digestiva : ABCD = Brazilian archives of digestive surgery · 2024
    Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Hospital volume following major surgery for gastric cancer determines in-hospital mortality rate and failure to rescue: a nation-wide study based on German billing data (2009-2017).Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2021
    Article
  14. Article
  15. Article
  16. Article
  17. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Ulrike NimptschDepartment for Structural Advancement and Quality Management in Health Care, Technische Universität Berlin, Berlin, Germany. ulrike.nimptsch@tu-berlin.de.ORCID http://orcid.org/0000-0002-4292-5162
Thomas HaistKlinik für Allgemein- und Viszeralchirurgie, Sana Klinikum Offenbach GmbH, Offenbach, Germany.
Ines GockelKlinik und Poliklinik für Viszeral-, Transplantations-, Thorax- und Gefäßchirurgie, Universitätsklinikum Leipzig, Leipzig, Germany.
Thomas ManskyDepartment for Structural Advancement and Quality Management in Health Care, Technische Universität Berlin, Berlin, Germany.
Dietmar LorenzKlinik für Allgemein-, Viszeral- und Thoraxchirurgie, Klinikum Darmstadt GmbH, Darmstadt, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis observational study explored the association between hospital volume and short-term outcome following gastric resections for non-bariatric indication, aiming to contribute to the discussion on centralization of complex visceral surgery in Germany.

methodsBased on complete national hospital discharge data from 2010 to 2015, the association between hospital volume and in-hospital mortality was evaluated according to volume quintiles and volume deciles. Case-mix differences regarding surgical indication, age, sex, and comorbidities were considered for risk adjustment. In addition, rates of major complications and failure to rescue were analyzed across hospital volume categories.

resultsInpatient episodes (72,528) with gastric resection were analyzed. Risk-adjusted mortality in patients treated in very low volume hospitals (median volume of 5 surgeries per year) was higher (12.0% [95% CI 11.4 to 12.5]) compared to those treated in very high volume hospitals (50 surgeries per year; 10.6% [10.0 to 11.1]). Failure to rescue patients with complications was 28.1% [27.0 to 29.3] in very low volume hospitals and 22.7% [21.6 to 23.8] in very high volume hospitals. Differences were similar within the subgroup of patients operated for gastric cancer.

conclusionsTreatment in very high volume hospitals is associated with a lower in-hospital mortality compared to treatment in very low volume hospitals. This effect seems to be determined by the ability to rescue patients who experience complications. As the observed benefit is only related to very high volumes, the results do not clearly indicate that centralization may improve short-term results substantially, unless a very high degree of centralization would be achieved. Possibly, further research focusing on other outcome measures, such as clinical processes or long-term results, might lead to divergent conclusions.

Indexed as

AgedDiagnosis-Related GroupsFailure to Rescue, Health CareFemaleGastrectomyGermanyHospitalizationHospital MortalityHospitals, High-VolumeHumansMaleMiddle AgedOutcome Assessment, Health CarePostoperative ComplicationsStomach DiseasesCentralizationFailure to rescueGastric surgeryHospital discharge dataVolume outcome relation

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.